Pandas Profiling Report

Dataset statistics

Number of variables	32
Number of observations	121
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	30.4 KiB
Average record size in memory	257.1 B

Variable types

Numeric	12
Categorical	20

Alerts

`anupam_present` has constant value "1"	Constant
`brand_name` has a high cardinality: 121 distinct values	High cardinality
`description` has a high cardinality: 121 distinct values	High cardinality
`episode_number` is highly overall correlated with `startup_number` and 6 other fields	High correlation
`startup_number` is highly overall correlated with `episode_number` and 6 other fields	High correlation
`startup_ask_amount_lakhs` is highly overall correlated with `startup_ask_valuation`	High correlation
`startup_ask_percentage` is highly overall correlated with `startup_ask_valuation`	High correlation
`startup_ask_valuation` is highly overall correlated with `startup_ask_amount_lakhs` and 1 other fields	High correlation
`deal_amount_lakhs` is highly overall correlated with `deal_equity` and 6 other fields	High correlation
`deal_equity` is highly overall correlated with `deal_amount_lakhs` and 5 other fields	High correlation
`deal_valuation` is highly overall correlated with `deal_amount_lakhs` and 4 other fields	High correlation
`loan_amount` is highly overall correlated with `loan_element_present`	High correlation
`sharks_offering` is highly overall correlated with `deal_amount_lakhs` and 10 other fields	High correlation
`amount_per_shark` is highly overall correlated with `deal_amount_lakhs` and 5 other fields	High correlation
`equity_per_shark` is highly overall correlated with `deal_amount_lakhs` and 4 other fields	High correlation
`deal_offered` is highly overall correlated with `deal_amount_lakhs` and 3 other fields	High correlation
`loan_element_present` is highly overall correlated with `loan_amount`	High correlation
`rannvijay_present` is highly overall correlated with `abish_present`	High correlation
`abish_present` is highly overall correlated with `rannvijay_present`	High correlation
`aman_present` is highly overall correlated with `episode_number` and 3 other fields	High correlation
`aman_invested` is highly overall correlated with `deal_amount_lakhs` and 1 other fields	High correlation
`anupam_invested` is highly overall correlated with `sharks_offering`	High correlation
`ashneer_present` is highly overall correlated with `episode_number` and 3 other fields	High correlation
`ashneer_invested` is highly overall correlated with `sharks_offering`	High correlation
`ghazal_present` is highly overall correlated with `episode_number` and 3 other fields	High correlation
`namita_present` is highly overall correlated with `episode_number` and 1 other fields	High correlation
`namita_invested` is highly overall correlated with `sharks_offering`	High correlation
`peyush_present` is highly overall correlated with `episode_number` and 1 other fields	High correlation
`peyush_invested` is highly overall correlated with `sharks_offering`	High correlation
`vineeta_present` is highly overall correlated with `episode_number` and 1 other fields	High correlation
`loan_element_present` is highly imbalanced (61.8%)	Imbalance
`rannvijay_present` is highly imbalanced (79.0%)	Imbalance
`abish_present` is highly imbalanced (79.0%)	Imbalance
`ghazal_invested` is highly imbalanced (68.1%)	Imbalance
`namita_present` is highly imbalanced (56.1%)	Imbalance
`startup_number` is uniformly distributed	Uniform
`brand_name` is uniformly distributed	Uniform
`description` is uniformly distributed	Uniform
`startup_number` has unique values	Unique
`brand_name` has unique values	Unique
`description` has unique values	Unique
`deal_amount_lakhs` has 54 (44.6%) zeros	Zeros
`deal_equity` has 54 (44.6%) zeros	Zeros
`deal_valuation` has 55 (45.5%) zeros	Zeros
`loan_amount` has 112 (92.6%) zeros	Zeros
`sharks_offering` has 54 (44.6%) zeros	Zeros
`amount_per_shark` has 54 (44.6%) zeros	Zeros
`equity_per_shark` has 54 (44.6%) zeros	Zeros

Reproduction

Analysis started	2023-05-28 06:48:39.731537
Analysis finished	2023-05-28 06:48:56.610192
Duration	16.88 seconds
Software version	pandas-profiling v3.6.6
Download configuration	config.json

episode_number
Real number (ℝ)

Distinct	36
Distinct (%)	29.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	19.305785

Minimum	1
Maximum	36
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.1 KiB

Quantile statistics

Minimum	1
5-th percentile	3
Q1	11
median	19
Q3	28
95-th percentile	35
Maximum	36
Range	35
Interquartile range (IQR)	17

Descriptive statistics

Standard deviation	10.375326
Coefficient of variation (CV)	0.53742055
Kurtosis	-1.1651326
Mean	19.305785
Median Absolute Deviation (MAD)	9
Skewness	-0.094792331
Sum	2336
Variance	107.64738
Monotonicity	Increasing

Histogram with fixed size bins (bins=36)

Value	Count	Frequency (%)
19	4	3.3%
16	4	3.3%
34	4	3.3%
33	4	3.3%
32	4	3.3%
31	4	3.3%
30	4	3.3%
27	4	3.3%
23	4	3.3%
22	4	3.3%
Other values (26)	81	66.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	3	2.5%
2	3	2.5%
3	3	2.5%
4	3	2.5%
5	3	2.5%
6	3	2.5%
7	3	2.5%
8	3	2.5%
9	3	2.5%
10	3	2.5%

Value	Count	Frequency (%)
36	4	3.3%
35	3	2.5%
34	4	3.3%
33	4	3.3%
32	4	3.3%
31	4	3.3%
30	4	3.3%
29	3	2.5%
28	3	2.5%
27	4	3.3%

startup_number
Real number (ℝ)

HIGH CORRELATION UNIFORM UNIQUE

Distinct	121
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	61

Minimum	1
Maximum	121
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.1 KiB

Quantile statistics

Minimum	1
5-th percentile	7
Q1	31
median	61
Q3	91
95-th percentile	115
Maximum	121
Range	120
Interquartile range (IQR)	60

Descriptive statistics

Standard deviation	35.073732
Coefficient of variation (CV)	0.57497921
Kurtosis	-1.2
Mean	61
Median Absolute Deviation (MAD)	30
Skewness	0
Sum	7381
Variance	1230.1667
Monotonicity	Strictly increasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1	1	0.8%
62	1	0.8%
90	1	0.8%
89	1	0.8%
88	1	0.8%
87	1	0.8%
86	1	0.8%
85	1	0.8%
84	1	0.8%
83	1	0.8%
Other values (111)	111	91.7%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	1	0.8%
2	1	0.8%
3	1	0.8%
4	1	0.8%
5	1	0.8%
6	1	0.8%
7	1	0.8%
8	1	0.8%
9	1	0.8%
10	1	0.8%

Value	Count	Frequency (%)
121	1	0.8%
120	1	0.8%
119	1	0.8%
118	1	0.8%
117	1	0.8%
116	1	0.8%
115	1	0.8%
114	1	0.8%
113	1	0.8%
112	1	0.8%

brand_name
Categorical

HIGH CARDINALITY UNIFORM UNIQUE

Distinct	121
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

BluePine Industries	1
The State Plate	1
Kunafa World	1
Humpy A2	1
Insurance Samadhan	1
Other values (116)	116

Length

Max length	30
Median length	19
Mean length	11.669421
Min length	3

Characters and Unicode

Total characters	1412
Distinct characters	59
Distinct categories	6 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	121 ?
Unique (%)	100.0%

Sample

1st row	BluePine Industries
2nd row	Booz scooters
3rd row	Heart up my Sleeves
4th row	Tagz Foods
5th row	Head and Heart

Common Values

Value	Count	Frequency (%)
BluePine Industries	1	0.8%
The State Plate	1	0.8%
Kunafa World	1	0.8%
Humpy A2	1	0.8%
Insurance Samadhan	1	0.8%
Aliste Technologies	1	0.8%
Watt Technovations	1	0.8%
Theka Coffee	1	0.8%
Rare Planet	1	0.8%
Julaa Automation	1	0.8%
Other values (111)	111	91.7%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
the	5	2.2%
foods	4	1.7%
india	4	1.7%
and	3	1.3%
heart	2	0.9%
technologies	2	0.9%
project	2	0.9%
labs	2	0.9%
kitchen	2	0.9%
beyond	2	0.9%
Other values (198)	203	87.9%

Most occurring characters

Value	Count	Frequency (%)
e	121	8.6%
a	120	8.5%
	110	7.8%
o	98	6.9%
i	81	5.7%
n	80	5.7%
r	73	5.2%
s	58	4.1%
t	55	3.9%
d	48	3.4%
Other values (49)	568	40.2%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	1034	73.2%
Uppercase Letter	255	18.1%
Space Separator	110	7.8%
Decimal Number	6	0.4%
Other Punctuation	5	0.4%
Dash Punctuation	2	0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	121	11.7%
a	120	11.6%
o	98	9.5%
i	81	7.8%
n	80	7.7%
r	73	7.1%
s	58	5.6%
t	55	5.3%
d	48	4.6%
l	39	3.8%
Other values (16)	261	25.2%

Uppercase Letter

Value	Count	Frequency (%)
S	26	10.2%
A	21	8.2%
T	21	8.2%
M	17	6.7%
P	16	6.3%
F	14	5.5%
B	14	5.5%
C	13	5.1%
I	12	4.7%
H	11	4.3%
Other values (14)	90	35.3%

Decimal Number

Value	Count	Frequency (%)
2	2	33.3%
7	1	16.7%
0	1	16.7%
5	1	16.7%
6	1	16.7%

Other Punctuation

Value	Count	Frequency (%)
'	4	80.0%
.	1	20.0%

Space Separator

Value	Count	Frequency (%)
	110	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1289	91.3%
Common	123	8.7%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	121	9.4%
a	120	9.3%
o	98	7.6%
i	81	6.3%
n	80	6.2%
r	73	5.7%
s	58	4.5%
t	55	4.3%
d	48	3.7%
l	39	3.0%
Other values (40)	516	40.0%

Common

Value	Count	Frequency (%)
	110	89.4%
'	4	3.3%
2	2	1.6%
-	2	1.6%
.	1	0.8%
7	1	0.8%
0	1	0.8%
5	1	0.8%
6	1	0.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1412	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	121	8.6%
a	120	8.5%
	110	7.8%
o	98	6.9%
i	81	5.7%
n	80	5.7%
r	73	5.2%
s	58	4.1%
t	55	3.9%
d	48	3.4%
Other values (49)	568	40.2%

description
Categorical

HIGH CARDINALITY UNIFORM UNIQUE

Distinct	121
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

Frozen Momos	1
Delicacies	1
Kunafa	1
Organic Milk Products	1
Insurance Solutions	1
Other values (116)	116

Length

Max length	48
Median length	32
Mean length	18.421488
Min length	2

Characters and Unicode

Total characters	2229
Distinct characters	53
Distinct categories	6 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	121 ?
Unique (%)	100.0%

Sample

1st row	Frozen Momos
2nd row	Renting e-bike for mobility in private spaces
3rd row	Detachable Sleeves
4th row	Healthy Potato Chips
5th row	Brain Development Course

Common Values

Value	Count	Frequency (%)
Frozen Momos	1	0.8%
Delicacies	1	0.8%
Kunafa	1	0.8%
Organic Milk Products	1	0.8%
Insurance Solutions	1	0.8%
Automation Solutions	1	0.8%
Ventilated PPE Kits	1	0.8%
Coffee Products	1	0.8%
Handicrafts	1	0.8%
Automatic Cradle	1	0.8%
Other values (111)	111	91.7%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
products	9	3.0%
app	8	2.6%
solutions	6	2.0%
food	5	1.7%
healthy	4	1.3%
for	4	1.3%
and	4	1.3%
smart	4	1.3%
device	3	1.0%
ayurvedic	3	1.0%
Other values (231)	253	83.5%

Most occurring characters

Value	Count	Frequency (%)
e	223	10.0%
	182	8.2%
a	152	6.8%
t	146	6.6%
o	141	6.3%
i	137	6.1%
r	130	5.8%
s	129	5.8%
n	115	5.2%
l	98	4.4%
Other values (43)	776	34.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	1758	78.9%
Uppercase Letter	275	12.3%
Space Separator	182	8.2%
Dash Punctuation	11	0.5%
Decimal Number	2	0.1%
Other Punctuation	1	< 0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	223	12.7%
a	152	8.6%
t	146	8.3%
o	141	8.0%
i	137	7.8%
r	130	7.4%
s	129	7.3%
n	115	6.5%
l	98	5.6%
c	74	4.2%
Other values (15)	413	23.5%

Uppercase Letter

Value	Count	Frequency (%)
S	35	12.7%
P	32	11.6%
A	25	9.1%
C	22	8.0%
F	20	7.3%
D	18	6.5%
E	14	5.1%
I	13	4.7%
B	13	4.7%
H	13	4.7%
Other values (13)	70	25.5%

Decimal Number

Value	Count	Frequency (%)
8	1	50.0%
0	1	50.0%

Space Separator

Value	Count	Frequency (%)
	182	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	11	100.0%

Other Punctuation

Value	Count	Frequency (%)
&	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	2033	91.2%
Common	196	8.8%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	223	11.0%
a	152	7.5%
t	146	7.2%
o	141	6.9%
i	137	6.7%
r	130	6.4%
s	129	6.3%
n	115	5.7%
l	98	4.8%
c	74	3.6%
Other values (38)	688	33.8%

Common

Value	Count	Frequency (%)
	182	92.9%
-	11	5.6%
&	1	0.5%
8	1	0.5%
0	1	0.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	2229	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	223	10.0%
	182	8.2%
a	152	6.8%
t	146	6.6%
o	141	6.3%
i	137	6.1%
r	130	5.8%
s	129	5.8%
n	115	5.2%
l	98	4.4%
Other values (43)	776	34.8%

deal_offered
Categorical

Distinct	2
Distinct (%)	1.7%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

1	68
0	53

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	121
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	0

Common Values

Value	Count	Frequency (%)
1	68	56.2%
0	53	43.8%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
1	68	56.2%
0	53	43.8%

Most occurring characters

Value	Count	Frequency (%)
1	68	56.2%
0	53	43.8%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	121	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	68	56.2%
0	53	43.8%

Most occurring scripts

Value	Count	Frequency (%)
Common	121	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	68	56.2%
0	53	43.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	121	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	68	56.2%
0	53	43.8%

startup_ask_amount_lakhs
Real number (ℝ)

Distinct	26
Distinct (%)	21.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	312.33885

Minimum	0.00101
Maximum	30000
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.1 KiB

Quantile statistics

Minimum	0.00101
5-th percentile	25
Q1	45
median	50
Q3	80
95-th percentile	125
Maximum	30000
Range	29999.999
Interquartile range (IQR)	35

Descriptive statistics

Standard deviation	2721.6405
Coefficient of variation (CV)	8.713743
Kurtosis	120.9505
Mean	312.33885
Median Absolute Deviation (MAD)	20
Skewness	10.99666
Sum	37793.001
Variance	7407326.9
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=26)

Value	Count	Frequency (%)
50	32	26.4%
100	18	14.9%
75	14	11.6%
30	9	7.4%
40	9	7.4%
80	5	4.1%
60	4	3.3%
35	4	3.3%
150	3	2.5%
45	3	2.5%
Other values (16)	20	16.5%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0.00101	1	0.8%
5	1	0.8%
10	1	0.8%
15	1	0.8%
20	2	1.7%
25	2	1.7%
30	9	7.4%
35	4	3.3%
40	9	7.4%
45	3	2.5%

Value	Count	Frequency (%)
30000	1	0.8%
300	1	0.8%
200	1	0.8%
150	3	2.5%
125	1	0.8%
120	1	0.8%
100	18	14.9%
90	2	1.7%
80	5	4.1%
75	14	11.6%

startup_ask_percentage
Real number (ℝ)

Distinct	19
Distinct (%)	15.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5.0833058

Minimum	0.25
Maximum	25
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.1 KiB

Quantile statistics

Minimum	0.25
5-th percentile	1
Q1	2
median	5
Q3	7
95-th percentile	10
Maximum	25
Range	24.75
Interquartile range (IQR)	5

Descriptive statistics

Standard deviation	3.8825536
Coefficient of variation (CV)	0.76378517
Kurtosis	6.2950925
Mean	5.0833058
Median Absolute Deviation (MAD)	2.5
Skewness	1.9426984
Sum	615.08
Variance	15.074222
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=19)

Value	Count	Frequency (%)
5	30	24.8%
10	16	13.2%
1	14	11.6%
2	14	11.6%
4	11	9.1%
3	9	7.4%
8	5	4.1%
2.5	5	4.1%
7.5	5	4.1%
15	2	1.7%
Other values (9)	10	8.3%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0.25	1	0.8%
0.33	1	0.8%
1	14	11.6%
1.25	1	0.8%
1.75	1	0.8%
2	14	11.6%
2.5	5	4.1%
3	9	7.4%
3.5	1	0.8%
4	11	9.1%

Value	Count	Frequency (%)
25	1	0.8%
20	1	0.8%
15	2	1.7%
10	16	13.2%
8	5	4.1%
7.5	5	4.1%
7	2	1.7%
6	1	0.8%
5	30	24.8%
4	11	9.1%

startup_ask_valuation
Real number (ℝ)

Distinct	50
Distinct (%)	41.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	4230.1827

Minimum	0.01
Maximum	120000
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.1 KiB

Quantile statistics

Minimum	0.01
5-th percentile	300
Q1	666.67
median	1333.33
Q3	3000
95-th percentile	10000
Maximum	120000
Range	119999.99
Interquartile range (IQR)	2333.33

Descriptive statistics

Standard deviation	12329.895
Coefficient of variation (CV)	2.9147428
Kurtosis	66.855418
Mean	4230.1827
Median Absolute Deviation (MAD)	833.33
Skewness	7.5982775
Sum	511852.11
Variance	1.520263 × 10⁸
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1000	11	9.1%
500	11	9.1%
10000	8	6.6%
2000	7	5.8%
2500	6	5.0%
1250	5	4.1%
1875	5	4.1%
1500	5	4.1%
5000	5	4.1%
400	4	3.3%
Other values (40)	54	44.6%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0.01	1	0.8%
50	1	0.8%
100	1	0.8%
200	1	0.8%
250	1	0.8%
266.67	1	0.8%
300	3	2.5%
400	4	3.3%
470	1	0.8%
500	11	9.1%

Value	Count	Frequency (%)
120000	1	0.8%
45000	1	0.8%
40000	1	0.8%
30000	1	0.8%
10000	8	6.6%
8000	1	0.8%
7500	2	1.7%
7000	1	0.8%
6500	1	0.8%
5714	1	0.8%

deal_amount_lakhs
Real number (ℝ)

HIGH CORRELATION ZEROS

Distinct	22
Distinct (%)	18.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	31.925629

Minimum	0
Maximum	150
Zeros	54
Zeros (%)	44.6%
Negative	0
Negative (%)	0.0%
Memory size	1.1 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	21
Q3	50
95-th percentile	100
Maximum	150
Range	150
Interquartile range (IQR)	50

Descriptive statistics

Standard deviation	36.847011
Coefficient of variation (CV)	1.1541515
Kurtosis	-0.30997096
Mean	31.925629
Median Absolute Deviation (MAD)	21
Skewness	0.84552667
Sum	3863.0011
Variance	1357.7022
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=22)

Value	Count	Frequency (%)
0	54	44.6%
50	15	12.4%
100	12	9.9%
75	7	5.8%
40	6	5.0%
25	4	3.3%
30	4	3.3%
60	3	2.5%
80	2	1.7%
10	2	1.7%
Other values (12)	12	9.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	54	44.6%
5 × 10^-5	1	0.8%
0.00101	1	0.8%
1	1	0.8%
10	2	1.7%
20	1	0.8%
21	1	0.8%
25	4	3.3%
30	4	3.3%
35	1	0.8%

Value	Count	Frequency (%)
150	1	0.8%
105	1	0.8%
100	12	9.9%
80	2	1.7%
75	7	5.8%
70	1	0.8%
65	1	0.8%
60	3	2.5%
56	1	0.8%
50	15	12.4%

deal_equity
Real number (ℝ)

HIGH CORRELATION ZEROS

Distinct	28
Distinct (%)	23.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	8.7994215

Minimum	0
Maximum	75
Zeros	54
Zeros (%)	44.6%
Negative	0
Negative (%)	0.0%
Memory size	1.1 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	3
Q3	15
95-th percentile	33.3
Maximum	75
Range	75
Interquartile range (IQR)	15

Descriptive statistics

Standard deviation	12.948175
Coefficient of variation (CV)	1.4714802
Kurtosis	6.0176742
Mean	8.7994215
Median Absolute Deviation (MAD)	3
Skewness	2.1467433
Sum	1064.73
Variance	167.65522
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=28)

Value	Count	Frequency (%)
0	54	44.6%
15	9	7.4%
20	7	5.8%
10	7	5.8%
6	5	4.1%
4	5	4.1%
25	4	3.3%
3	4	3.3%
30	3	2.5%
50	2	1.7%
Other values (18)	21	17.4%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	54	44.6%
1	1	0.8%
1.5	1	0.8%
2	1	0.8%
2.5	1	0.8%
2.68	1	0.8%
2.75	1	0.8%
3	4	3.3%
3.5	1	0.8%
4	5	4.1%

Value	Count	Frequency (%)
75	1	0.8%
50	2	1.7%
40	2	1.7%
35	1	0.8%
33.3	1	0.8%
30	3	2.5%
25	4	3.3%
24	2	1.7%
21	1	0.8%
20	7	5.8%

deal_valuation
Real number (ℝ)

HIGH CORRELATION ZEROS

Distinct	40
Distinct (%)	33.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	473.77083

Minimum	0
Maximum	6666.67
Zeros	55
Zeros (%)	45.5%
Negative	0
Negative (%)	0.0%
Memory size	1.1 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	100
Q3	500
95-th percentile	2500
Maximum	6666.67
Range	6666.67
Interquartile range (IQR)	500

Descriptive statistics

Standard deviation	925.69347
Coefficient of variation (CV)	1.9538845
Kurtosis	17.139564
Mean	473.77083
Median Absolute Deviation (MAD)	100
Skewness	3.5170249
Sum	57326.27
Variance	856908.4
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=40)

Value	Count	Frequency (%)
0	55	45.5%
500	5	4.1%
1000	5	4.1%
100	4	3.3%
2500	4	3.3%
200	3	2.5%
666.67	3	2.5%
250	3	2.5%
166.67	2	1.7%
1333.33	2	1.7%
Other values (30)	35	28.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	55	45.5%
0.03	1	0.8%
25	1	0.8%
33.33	1	0.8%
80	1	0.8%
83.33	1	0.8%
100	4	3.3%
125	1	0.8%
133.33	2	1.7%
142.86	1	0.8%

Value	Count	Frequency (%)
6666.67	1	0.8%
3500	1	0.8%
2798.51	1	0.8%
2545.45	1	0.8%
2500	4	3.3%
2166.67	1	0.8%
2000	1	0.8%
1666.67	2	1.7%
1500	1	0.8%
1428.57	1	0.8%

loan_element_present
Categorical

HIGH CORRELATION IMBALANCE

Distinct	2
Distinct (%)	1.7%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

0	112
1	9

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	121
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	112	92.6%
1	9	7.4%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
0	112	92.6%
1	9	7.4%

Most occurring characters

Value	Count	Frequency (%)
0	112	92.6%
1	9	7.4%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	121	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	112	92.6%
1	9	7.4%

Most occurring scripts

Value	Count	Frequency (%)
Common	121	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	112	92.6%
1	9	7.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	121	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	112	92.6%
1	9	7.4%

loan_amount
Real number (ℝ)

HIGH CORRELATION ZEROS

Distinct	7
Distinct (%)	5.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2.9008264

Minimum	0
Maximum	99
Zeros	112
Zeros (%)	92.6%
Negative	0
Negative (%)	0.0%
Memory size	1.1 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	25
Maximum	99
Range	99
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	12.150724
Coefficient of variation (CV)	4.188711
Kurtosis	35.872499
Mean	2.9008264
Median Absolute Deviation (MAD)	0
Skewness	5.5124559
Sum	351
Variance	147.64008
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=7)

Value	Count	Frequency (%)
0	112	92.6%
30	2	1.7%
25	2	1.7%
50	2	1.7%
99	1	0.8%
22	1	0.8%
20	1	0.8%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	112	92.6%
20	1	0.8%
22	1	0.8%
25	2	1.7%
30	2	1.7%
50	2	1.7%
99	1	0.8%

Value	Count	Frequency (%)
99	1	0.8%
50	2	1.7%
30	2	1.7%
25	2	1.7%
22	1	0.8%
20	1	0.8%
0	112	92.6%

rannvijay_present
Categorical

HIGH CORRELATION IMBALANCE

Distinct	2
Distinct (%)	1.7%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

1	117
0	4

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	121
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	117	96.7%
0	4	3.3%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
1	117	96.7%
0	4	3.3%

Most occurring characters

Value	Count	Frequency (%)
1	117	96.7%
0	4	3.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	121	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	117	96.7%
0	4	3.3%

Most occurring scripts

Value	Count	Frequency (%)
Common	121	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	117	96.7%
0	4	3.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	121	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	117	96.7%
0	4	3.3%

abish_present
Categorical

HIGH CORRELATION IMBALANCE

Distinct	2
Distinct (%)	1.7%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

0	117
1	4

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	121
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	117	96.7%
1	4	3.3%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
0	117	96.7%
1	4	3.3%

Most occurring characters

Value	Count	Frequency (%)
0	117	96.7%
1	4	3.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	121	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	117	96.7%
1	4	3.3%

Most occurring scripts

Value	Count	Frequency (%)
Common	121	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	117	96.7%
1	4	3.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	121	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	117	96.7%
1	4	3.3%

aman_present
Categorical

Distinct	2
Distinct (%)	1.7%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

1	102
0	19

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	121
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	102	84.3%
0	19	15.7%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
1	102	84.3%
0	19	15.7%

Most occurring characters

Value	Count	Frequency (%)
1	102	84.3%
0	19	15.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	121	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	102	84.3%
0	19	15.7%

Most occurring scripts

Value	Count	Frequency (%)
Common	121	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	102	84.3%
0	19	15.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	121	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	102	84.3%
0	19	15.7%

aman_invested
Categorical

Distinct	2
Distinct (%)	1.7%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

0	92
1	29

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	121
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	92	76.0%
1	29	24.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
0	92	76.0%
1	29	24.0%

Most occurring characters

Value	Count	Frequency (%)
0	92	76.0%
1	29	24.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	121	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	92	76.0%
1	29	24.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	121	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	92	76.0%
1	29	24.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	121	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	92	76.0%
1	29	24.0%

anupam_present
Categorical

Distinct	1
Distinct (%)	0.8%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

1	121

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	121
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	121	100.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
1	121	100.0%

Most occurring characters

Value	Count	Frequency (%)
1	121	100.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	121	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	121	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	121	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	121	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	121	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	121	100.0%

anupam_invested
Categorical

Distinct	2
Distinct (%)	1.7%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

0	97
1	24

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	121
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	1
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	97	80.2%
1	24	19.8%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
0	97	80.2%
1	24	19.8%

Most occurring characters

Value	Count	Frequency (%)
0	97	80.2%
1	24	19.8%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	121	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	97	80.2%
1	24	19.8%

Most occurring scripts

Value	Count	Frequency (%)
Common	121	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	97	80.2%
1	24	19.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	121	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	97	80.2%
1	24	19.8%

ashneer_present
Categorical

Distinct	2
Distinct (%)	1.7%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

1	98
0	23

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	121
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	98	81.0%
0	23	19.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
1	98	81.0%
0	23	19.0%

Most occurring characters

Value	Count	Frequency (%)
1	98	81.0%
0	23	19.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	121	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	98	81.0%
0	23	19.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	121	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	98	81.0%
0	23	19.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	121	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	98	81.0%
0	23	19.0%

ashneer_invested
Categorical

Distinct	2
Distinct (%)	1.7%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

0	100
1	21

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	121
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	0
4th row	1
5th row	0

Common Values

Value	Count	Frequency (%)
0	100	82.6%
1	21	17.4%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
0	100	82.6%
1	21	17.4%

Most occurring characters

Value	Count	Frequency (%)
0	100	82.6%
1	21	17.4%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	121	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	100	82.6%
1	21	17.4%

Most occurring scripts

Value	Count	Frequency (%)
Common	121	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	100	82.6%
1	21	17.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	121	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	100	82.6%
1	21	17.4%

ghazal_present
Categorical

Distinct	2
Distinct (%)	1.7%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

0	95
1	26

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	121
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	95	78.5%
1	26	21.5%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
0	95	78.5%
1	26	21.5%

Most occurring characters

Value	Count	Frequency (%)
0	95	78.5%
1	26	21.5%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	121	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	95	78.5%
1	26	21.5%

Most occurring scripts

Value	Count	Frequency (%)
Common	121	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	95	78.5%
1	26	21.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	121	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	95	78.5%
1	26	21.5%

ghazal_invested
Categorical

Distinct	2
Distinct (%)	1.7%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

0	114
1	7

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	121
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	114	94.2%
1	7	5.8%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
0	114	94.2%
1	7	5.8%

Most occurring characters

Value	Count	Frequency (%)
0	114	94.2%
1	7	5.8%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	121	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	114	94.2%
1	7	5.8%

Most occurring scripts

Value	Count	Frequency (%)
Common	121	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	114	94.2%
1	7	5.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	121	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	114	94.2%
1	7	5.8%

namita_present
Categorical

HIGH CORRELATION IMBALANCE

Distinct	2
Distinct (%)	1.7%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

1	110
0	11

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	121
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	110	90.9%
0	11	9.1%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
1	110	90.9%
0	11	9.1%

Most occurring characters

Value	Count	Frequency (%)
1	110	90.9%
0	11	9.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	121	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	110	90.9%
0	11	9.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	121	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	110	90.9%
0	11	9.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	121	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	110	90.9%
0	11	9.1%

namita_invested
Categorical

Distinct	2
Distinct (%)	1.7%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

0	97
1	24

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	121
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	97	80.2%
1	24	19.8%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
0	97	80.2%
1	24	19.8%

Most occurring characters

Value	Count	Frequency (%)
0	97	80.2%
1	24	19.8%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	121	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	97	80.2%
1	24	19.8%

Most occurring scripts

Value	Count	Frequency (%)
Common	121	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	97	80.2%
1	24	19.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	121	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	97	80.2%
1	24	19.8%

peyush_present
Categorical

Distinct	2
Distinct (%)	1.7%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

1	92
0	29

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	121
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
1	92	76.0%
0	29	24.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
1	92	76.0%
0	29	24.0%

Most occurring characters

Value	Count	Frequency (%)
1	92	76.0%
0	29	24.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	121	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	92	76.0%
0	29	24.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	121	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	92	76.0%
0	29	24.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	121	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	92	76.0%
0	29	24.0%

peyush_invested
Categorical

Distinct	2
Distinct (%)	1.7%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

0	93
1	28

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	121
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	93	76.9%
1	28	23.1%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
0	93	76.9%
1	28	23.1%

Most occurring characters

Value	Count	Frequency (%)
0	93	76.9%
1	28	23.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	121	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	93	76.9%
1	28	23.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	121	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	93	76.9%
1	28	23.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	121	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	93	76.9%
1	28	23.1%

vineeta_present
Categorical

Distinct	2
Distinct (%)	1.7%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

1	70
0	51

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	121
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	70	57.9%
0	51	42.1%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
1	70	57.9%
0	51	42.1%

Most occurring characters

Value	Count	Frequency (%)
1	70	57.9%
0	51	42.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	121	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	70	57.9%
0	51	42.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	121	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	70	57.9%
0	51	42.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	121	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	70	57.9%
0	51	42.1%

vineeta_invested
Categorical

Distinct	2
Distinct (%)	1.7%
Missing	0
Missing (%)	0.0%
Memory size	1.1 KiB

0	105
1	16

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	121
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	105	86.8%
1	16	13.2%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
0	105	86.8%
1	16	13.2%

Most occurring characters

Value	Count	Frequency (%)
0	105	86.8%
1	16	13.2%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	121	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	105	86.8%
1	16	13.2%

Most occurring scripts

Value	Count	Frequency (%)
Common	121	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	105	86.8%
1	16	13.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	121	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	105	86.8%
1	16	13.2%

sharks_offering
Real number (ℝ)

HIGH CORRELATION ZEROS

Distinct	6
Distinct (%)	5.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.231405

Minimum	0
Maximum	5
Zeros	54
Zeros (%)	44.6%
Negative	0
Negative (%)	0.0%
Memory size	1.1 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	1
Q3	2
95-th percentile	4
Maximum	5
Range	5
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	1.4068898
Coefficient of variation (CV)	1.1425078
Kurtosis	0.0069148469
Mean	1.231405
Median Absolute Deviation (MAD)	1
Skewness	0.94817545
Sum	149
Variance	1.9793388
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
0	54	44.6%
1	22	18.2%
2	21	17.4%
3	15	12.4%
4	5	4.1%
5	4	3.3%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	54	44.6%
1	22	18.2%
2	21	17.4%
3	15	12.4%
4	5	4.1%
5	4	3.3%

Value	Count	Frequency (%)
5	4	3.3%
4	5	4.1%
3	15	12.4%
2	21	17.4%
1	22	18.2%
0	54	44.6%

amount_per_shark
Real number (ℝ)

HIGH CORRELATION ZEROS

Distinct	28
Distinct (%)	23.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	18.004134

Minimum	0
Maximum	100
Zeros	54
Zeros (%)	44.6%
Negative	0
Negative (%)	0.0%
Memory size	1.1 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	10
Q3	25
95-th percentile	70
Maximum	100
Range	100
Interquartile range (IQR)	25

Descriptive statistics

Standard deviation	23.51249
Coefficient of variation (CV)	1.3059495
Kurtosis	1.7346314
Mean	18.004134
Median Absolute Deviation (MAD)	10
Skewness	1.4518815
Sum	2178.5003
Variance	552.83717
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=28)

Value	Count	Frequency (%)
0	54	44.6%
25	12	9.9%
50	11	9.1%
20	7	5.8%
10	6	5.0%
40	3	2.5%
75	3	2.5%
100	2	1.7%
37.5	2	1.7%
33.33333333	2	1.7%
Other values (18)	19	15.7%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	54	44.6%
1.67 × 10^-5	1	0.8%
0.0002525	1	0.8%
1	1	0.8%
5	1	0.8%
7	1	0.8%
8.333333333	1	0.8%
10	6	5.0%
12.5	1	0.8%
13.33333333	1	0.8%

Value	Count	Frequency (%)
100	2	1.7%
80	1	0.8%
75	3	2.5%
70	1	0.8%
65	1	0.8%
50	11	9.1%
40	3	2.5%
37.5	2	1.7%
35	1	0.8%
33.33333333	2	1.7%

equity_per_shark
Real number (ℝ)

HIGH CORRELATION ZEROS

Distinct	35
Distinct (%)	28.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5.448595

Minimum	0
Maximum	75
Zeros	54
Zeros (%)	44.6%
Negative	0
Negative (%)	0.0%
Memory size	1.1 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	1.25
Q3	6
95-th percentile	25
Maximum	75
Range	75
Interquartile range (IQR)	6

Descriptive statistics

Standard deviation	10.651783
Coefficient of variation (CV)	1.9549596
Kurtosis	17.921125
Mean	5.448595
Median Absolute Deviation (MAD)	1.25
Skewness	3.7484669
Sum	659.28
Variance	113.46048
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=35)

Value	Count	Frequency (%)
0	54	44.6%
5	7	5.8%
3	5	4.1%
15	5	4.1%
1	4	3.3%
10	4	3.3%
2	4	3.3%
6	3	2.5%
25	3	2.5%
4	2	1.7%
Other values (25)	30	24.8%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	54	44.6%
0.75	1	0.8%
1	4	3.3%
1.2	1	0.8%
1.25	1	0.8%
1.333333333	1	0.8%
1.666666667	1	0.8%
1.75	1	0.8%
2	4	3.3%
2.5	2	1.7%

Value	Count	Frequency (%)
75	1	0.8%
50	1	0.8%
40	2	1.7%
25	3	2.5%
20	2	1.7%
17.5	1	0.8%
16.65	1	0.8%
15	5	4.1%
12.5	1	0.8%
12	1	0.8%

Auto

Heatmap
Table

	episode_number	startup_number	startup_ask_amount_lakhs	startup_ask_percentage	startup_ask_valuation	deal_amount_lakhs	deal_equity	deal_valuation	loan_amount	sharks_offering	amount_per_shark	equity_per_shark	deal_offered	loan_element_present	rannvijay_present	abish_present	aman_present	aman_invested	anupam_invested	ashneer_present	ashneer_invested	ghazal_present	ghazal_invested	namita_present	namita_invested	peyush_present	peyush_invested	vineeta_present	vineeta_invested
episode_number	1.000	1.000	0.118	-0.094	0.105	-0.199	-0.196	-0.191	0.005	-0.162	-0.212	-0.216	0.098	0.000	0.410	0.410	0.884	0.275	0.048	0.803	0.225	0.794	0.349	0.581	0.000	0.841	0.248	0.738	0.237
startup_number	1.000	1.000	0.117	-0.100	0.109	-0.206	-0.202	-0.197	0.004	-0.168	-0.218	-0.221	0.082	0.119	0.487	0.487	0.828	0.280	0.062	0.759	0.155	0.771	0.361	0.733	0.000	0.758	0.206	0.796	0.313
startup_ask_amount_lakhs	0.118	0.117	1.000	-0.436	0.781	-0.019	-0.329	-0.015	0.079	-0.272	-0.031	-0.291	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000
startup_ask_percentage	-0.094	-0.100	-0.436	1.000	-0.862	-0.121	0.218	-0.225	-0.074	0.025	-0.107	0.172	0.143	0.000	0.000	0.000	0.122	0.000	0.000	0.000	0.096	0.119	0.000	0.000	0.000	0.249	0.000	0.144	0.000
startup_ask_valuation	0.105	0.109	0.781	-0.862	1.000	0.057	-0.316	0.139	0.083	-0.159	0.042	-0.265	0.138	0.000	0.301	0.301	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.102	0.000	0.068	0.000
deal_amount_lakhs	-0.199	-0.206	-0.019	-0.121	0.057	1.000	0.770	0.951	0.107	0.847	0.935	0.764	0.876	0.165	0.000	0.000	0.000	0.510	0.492	0.000	0.357	0.000	0.000	0.000	0.427	0.114	0.482	0.057	0.414
deal_equity	-0.196	-0.202	-0.329	0.218	-0.316	0.770	1.000	0.673	0.205	0.827	0.777	0.976	0.612	0.327	0.000	0.000	0.000	0.313	0.453	0.000	0.254	0.000	0.239	0.195	0.265	0.000	0.355	0.000	0.450
deal_valuation	-0.191	-0.197	-0.015	-0.225	0.139	0.951	0.673	1.000	0.172	0.807	0.921	0.691	0.406	0.000	0.000	0.000	0.000	0.377	0.282	0.000	0.341	0.000	0.000	0.000	0.283	0.164	0.211	0.000	0.000
loan_amount	0.005	0.004	0.079	-0.074	0.083	0.107	0.205	0.172	1.000	0.080	0.213	0.257	0.172	0.987	0.288	0.288	0.000	0.000	0.000	0.000	0.170	0.000	0.000	0.119	0.000	0.000	0.308	0.000	0.000
sharks_offering	-0.162	-0.168	-0.272	0.025	-0.159	0.847	0.827	0.807	0.080	1.000	0.712	0.745	0.966	0.412	0.000	0.000	0.000	0.539	0.592	0.000	0.543	0.161	0.395	0.000	0.547	0.062	0.563	0.000	0.446
amount_per_shark	-0.212	-0.218	-0.031	-0.107	0.042	0.935	0.777	0.921	0.213	0.712	1.000	0.836	0.772	0.093	0.000	0.000	0.000	0.281	0.436	0.000	0.276	0.000	0.000	0.000	0.338	0.000	0.296	0.000	0.443
equity_per_shark	-0.216	-0.221	-0.291	0.172	-0.265	0.764	0.976	0.691	0.257	0.745	0.836	1.000	0.366	0.388	0.000	0.000	0.137	0.000	0.295	0.068	0.000	0.000	0.000	0.221	0.000	0.000	0.183	0.000	0.213
deal_offered	0.098	0.082	0.000	0.143	0.138	0.876	0.612	0.406	0.172	0.966	0.772	0.366	1.000	0.199	0.000	0.000	0.000	0.469	0.410	0.000	0.373	0.000	0.159	0.000	0.410	0.000	0.458	0.092	0.308
loan_element_present	0.000	0.119	0.000	0.000	0.000	0.165	0.327	0.000	0.987	0.412	0.093	0.388	0.199	1.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.156	0.000	0.000
rannvijay_present	0.410	0.487	0.000	0.000	0.301	0.000	0.000	0.000	0.288	0.000	0.000	0.000	0.000	0.000	1.000	0.870	0.000	0.000	0.000	0.311	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.063	0.000
abish_present	0.410	0.487	0.000	0.000	0.301	0.000	0.000	0.000	0.288	0.000	0.000	0.000	0.000	0.000	0.870	1.000	0.000	0.000	0.000	0.311	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.063	0.000
aman_present	0.884	0.828	0.000	0.122	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.137	0.000	0.000	0.000	0.000	1.000	0.196	0.000	0.861	0.141	0.795	0.420	0.033	0.000	0.196	0.067	0.335	0.000
aman_invested	0.275	0.280	0.000	0.000	0.000	0.510	0.313	0.377	0.000	0.539	0.281	0.000	0.469	0.000	0.000	0.000	0.196	1.000	0.158	0.176	0.265	0.204	0.035	0.000	0.265	0.000	0.000	0.186	0.000
anupam_invested	0.048	0.062	0.000	0.000	0.000	0.492	0.453	0.282	0.000	0.592	0.436	0.295	0.410	0.000	0.000	0.000	0.000	0.158	1.000	0.000	0.159	0.000	0.038	0.000	0.000	0.000	0.279	0.041	0.110
ashneer_present	0.803	0.759	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.068	0.000	0.000	0.311	0.311	0.861	0.176	0.000	1.000	0.172	0.692	0.366	0.073	0.000	0.231	0.059	0.383	0.000
ashneer_invested	0.225	0.155	0.000	0.096	0.000	0.357	0.254	0.341	0.170	0.543	0.276	0.000	0.373	0.000	0.000	0.000	0.141	0.265	0.159	0.172	1.000	0.056	0.000	0.000	0.000	0.000	0.165	0.074	0.150
ghazal_present	0.794	0.771	0.000	0.119	0.000	0.000	0.000	0.000	0.000	0.161	0.000	0.000	0.000	0.000	0.000	0.000	0.795	0.204	0.000	0.692	0.056	1.000	0.423	0.094	0.000	0.255	0.000	0.418	0.082
ghazal_invested	0.349	0.361	0.000	0.000	0.000	0.000	0.239	0.000	0.000	0.395	0.000	0.000	0.159	0.000	0.000	0.000	0.420	0.035	0.038	0.366	0.000	0.423	1.000	0.000	0.164	0.035	0.129	0.151	0.364
namita_present	0.581	0.733	0.000	0.000	0.000	0.000	0.195	0.000	0.119	0.000	0.000	0.221	0.000	0.000	0.000	0.000	0.033	0.000	0.000	0.073	0.000	0.094	0.000	1.000	0.080	0.112	0.000	0.224	0.000
namita_invested	0.000	0.000	0.000	0.000	0.000	0.427	0.265	0.283	0.000	0.547	0.338	0.000	0.410	0.000	0.000	0.000	0.000	0.265	0.000	0.000	0.000	0.000	0.164	0.080	1.000	0.000	0.113	0.041	0.110
peyush_present	0.841	0.758	0.000	0.249	0.102	0.114	0.000	0.164	0.000	0.062	0.000	0.000	0.000	0.000	0.000	0.000	0.196	0.000	0.000	0.231	0.000	0.255	0.035	0.112	0.000	1.000	0.271	0.452	0.122
peyush_invested	0.248	0.206	0.000	0.000	0.000	0.482	0.355	0.211	0.308	0.563	0.296	0.183	0.458	0.156	0.000	0.000	0.067	0.000	0.279	0.059	0.165	0.000	0.129	0.000	0.113	0.271	1.000	0.208	0.000
vineeta_present	0.738	0.796	0.000	0.144	0.068	0.057	0.000	0.000	0.000	0.000	0.000	0.000	0.092	0.000	0.063	0.063	0.335	0.186	0.041	0.383	0.074	0.418	0.151	0.224	0.041	0.452	0.208	1.000	0.296
vineeta_invested	0.237	0.313	0.000	0.000	0.000	0.414	0.450	0.000	0.000	0.446	0.443	0.213	0.308	0.000	0.000	0.000	0.000	0.000	0.110	0.000	0.150	0.082	0.364	0.000	0.110	0.122	0.000	0.296	1.000

Count
Matrix

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

First rows
Last rows

	episode_number	startup_number	brand_name	description	deal_offered	startup_ask_amount_lakhs	startup_ask_percentage	startup_ask_valuation	deal_amount_lakhs	deal_equity	deal_valuation	loan_element_present	loan_amount	rannvijay_present	aman_present	aman_invested	anupam_present	anupam_invested	ashneer_present	ashneer_invested	namita_present	vineeta_present	vineeta_invested	sharks_offering	amount_per_shark	equity_per_shark
0	1	1	BluePine Industries	Frozen Momos	1	50.0	5.00	1000.00	75.0	16.00	468.75	0	0	1	1	1	1	0	1	1	1	1	1	3	25.0	5.333333
1	1	2	Booz scooters	Renting e-bike for mobility in private spaces	1	40.0	15.00	266.67	40.0	50.00	80.00	0	0	1	1	0	1	0	1	1	1	1	1	2	20.0	25.000000
2	1	3	Heart up my Sleeves	Detachable Sleeves	1	25.0	10.00	250.00	25.0	30.00	83.33	0	0	1	1	0	1	1	1	0	1	1	1	2	12.5	15.000000
3	2	4	Tagz Foods	Healthy Potato Chips	1	70.0	1.00	7000.00	70.0	2.75	2545.45	0	0	1	1	0	1	0	1	1	1	1	0	1	70.0	2.750000
4	2	5	Head and Heart	Brain Development Course	0	50.0	5.00	1000.00	0.0	0.00	0.00	0	0	1	1	0	1	0	1	0	1	1	0	0	0.0	0.000000
5	2	6	Agro tourism	Tourism	0	50.0	5.00	1000.00	0.0	0.00	0.00	0	0	1	1	0	1	0	1	0	1	1	0	0	0.0	0.000000
6	3	7	Qzense Labs	Food Freshness Detector	0	100.0	0.25	40000.00	0.0	0.00	0.00	0	0	1	1	0	1	0	1	0	1	1	0	0	0.0	0.000000
7	3	8	Peeschute	Disposable Urine Bag	1	75.0	4.00	1875.00	75.0	6.00	1250.00	0	0	1	1	1	1	0	1	0	1	1	0	1	75.0	6.000000
8	3	9	NOCD	Energy Drink	1	50.0	2.00	2500.00	20.0	15.00	133.33	1	30	1	1	0	1	0	1	0	1	1	1	1	20.0	15.000000
9	4	10	Cosiq	Intelligent Skincare	1	50.0	7.50	666.67	50.0	25.00	200.00	0	0	1	1	0	1	1	1	0	1	1	1	2	25.0	12.500000

	episode_number	startup_number	brand_name	description	deal_offered	startup_ask_amount_lakhs	startup_ask_percentage	startup_ask_valuation	deal_amount_lakhs	deal_equity	deal_valuation	loan_element_present	loan_amount	rannvijay_present	abish_present	aman_present	aman_invested	anupam_present	anupam_invested	ashneer_present	ashneer_invested	ghazal_present	namita_present	namita_invested	peyush_present	peyush_invested	vineeta_present	vineeta_invested	sharks_offering	amount_per_shark	equity_per_shark
111	34	112	Twee in One	Reversible and convertible clothing	0	30.0	7.50	400.0	0.0	0.0	0.00	0	0	1	0	1	0	1	0	1	0	1	1	0	1	0	1	0	0	0.0	0.0
112	34	113	Green Protein	Plant-Based Protein	0	60.0	2.00	3000.0	0.0	0.0	0.00	0	0	1	0	1	0	1	0	1	0	1	1	0	1	0	1	0	0	0.0	0.0
113	34	114	On2Cook	Fastest Cooking Device	0	100.0	1.00	10000.0	0.0	0.0	0.00	0	0	1	0	1	0	1	0	1	0	1	1	0	1	0	1	0	0	0.0	0.0
114	35	115	Jain Shikanji	Lemonade	1	40.0	8.00	500.0	40.0	30.0	133.33	0	0	1	0	1	1	1	1	1	1	1	1	0	1	0	1	1	4	10.0	7.5
115	35	116	Woloo	Washroom Finder	0	50.0	4.00	1250.0	0.0	0.0	0.00	0	0	1	0	1	0	1	0	1	0	1	1	0	1	0	1	0	0	0.0	0.0
116	35	117	Elcare India	Carenting for Elders	0	100.0	2.50	4000.0	0.0	0.0	0.00	0	0	1	0	1	0	1	0	1	0	1	1	0	1	0	1	0	0	0.0	0.0
117	36	118	Sneakare	Shoe care and storage solutions	1	20.0	5.00	400.0	21.0	12.0	175.00	0	0	0	1	1	1	1	0	0	0	0	1	1	1	0	1	1	3	7.0	4.0
118	36	119	French Crown	Clothing Industry	0	150.0	0.33	45000.0	0.0	0.0	0.00	0	0	0	1	1	0	1	0	0	0	0	1	0	1	0	1	0	0	0.0	0.0
119	36	120	Store My Goods	Storage solutions	1	100.0	1.75	5714.0	100.0	4.0	2500.00	1	50	0	1	1	0	1	0	0	0	0	1	1	1	1	1	0	2	50.0	2.0
120	36	121	Devnagri	Translation platform	0	100.0	1.00	10000.0	0.0	0.0	0.00	0	0	0	1	1	0	1	0	0	0	0	1	0	1	0	1	0	0	0.0	0.0

Overview

Variables

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Decimal Number

Other Punctuation

Space Separator

Dash Punctuation

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Decimal Number

Space Separator

Dash Punctuation

Other Punctuation

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Common Values (Plot)